Let's build a recommendation system

Hemant Rakesh (~hemant56)



In this world of growing knowledge and technology, it is really hard to learn and understand everything see or read around us. And all we need is someone to refer the right resources (articles, blog, courses,etc) to begin with or to understand a certain way something works in a much clear way, with the help of the resources.

The AI/ML/DL community has made it simpler to perform the above tasks by introducing the concept of recommendation systems, and that's not all, the best part about it is that you can build your own recommendation system in your favorite and easy to use programming language -- Python.

Python is widely used to implement AI/ML and Deep learning algorithm. It has a lot of in-built package and modules which make it easy to understand and implement while programming.

Companies with recommendation systems: Amazon (recommends products), Facebook (recommends friends and posts), Ebay, FlipKart, Instagram, etc

The Workshop

The workshop will focus on the main concepts needed to build a deep learning model to build your own recommendation system. We will be building our own recommendation using Neural Networks, which is a deep learning concept, and other machine learning algorithms.

The recommendation system will be able to recommend:

  1. Courses, based on the faculty and teaching reviews.
  2. Suggest products to clients based on their search history

Topics to be covered: 1. Background (10 minutes) 2. Candidate Generation (30 minutes) 3. Retrieval, Scoring and Ranking (20 minutes) 4. Conclusion (10 minutes)


The prerequisites for the workshop are as follows:

  1. Basic understanding of ML and Deep Learning (Regression, Classification)
  2. Basic python programming
  3. Probability, Statistics, Linear Algebra

Speaker Info:

Hemant Rakesh a final year CSE student at NMIT, Bangalore; has keen interests in deep learning and is a reinforcement learning enthusiast. With prior experience in this field he loves to share his skills and knowledge to the community as he believes - " together we grow ". He also heads the machine learning club at nmit and has authored quite a few AI based blogs on Medium.

Hemant is also a research intern currently working on projects with Biomedical Engineering(10^-6 - 10^9) and Electronic System, Indian Institute of Science, Bangalore. He has a rich experience in computer vision, deep learning, reinforcement learning, neural computing and medical imaging and EEG based computation. Also, he has experience in building software tools in python for Image and neural analysis.

Speaker Links:

A list of few of my blogs can be found as follows:

1 Introduction to Neural Networks

2 Minimax or Maximin?

3 Distributed training using Tensorflow

LinkedIn: https://www.linkedin.com/in/hemant-rakesh-983b59129/

Github: https://www.github.com/hemantr05

Id: 1113
Section: Data Science, Machine Learning and AI
Type: Workshop
Target Audience: Intermediate
Last Updated: